Gentrification and Displacement: Modeling a Complex Urban Process

ABSTRACT

To shed some light on longstanding questions around gentrification, in this research we model environmental gentrification and gentrification-related displacement of residents. We do this through the development of an agent-based model of a simple urban region, considering different urban contexts and policy approaches to polluted facilities and the relationship of these policies with subsequent gentrification and displacement. We find that gentrification-related displacement is most likely, and most impactful, in urban regions characterized by high levels of density and low levels of residential segregation preferences. Displacement is far less prevalent in low-density regions, particularly those with high segregation preferences. We discuss the potential for different policy implications in these different urban contexts.

KEYWORDS:

• gentrification
• displacement
• agent-based model

Disclosure Statement

No potential conflict of interest was reported by the authors.

Notes

1. When residents have higher density preferences, modeled cities have higher density housing outcomes.

2. These eliminations can be thought of as people moving completely out of this city to another, or also as losses because of death, etc.

3. The gamma distribution is used because it is right skewed, as is the U.S. income distribution. Both distributions are constrained to be no less than zero. Data for the income variable was derived by the authors from the 2010 U.S. Census. Using the Census block level as the unit of analysis, we imputed a data set of individuals in the United States via the population of each census block, a random assignment of individual incomes based on the average income in each census block.

4. We thank an anonymous reviewer for suggestions about the utility function and the modeling strategy generally. After conducting sensitivity analyses, the model was altered to better capture the heterogeneity of agent decision-making. See the Appendix for more detail about the model.

5. As a first attempt to operationalize this concept in a simulation model, we arrived at this operationalization through testing. We set lower thresholds for gentrifiable and higher thresholds for gentrified, settling on these values as a good balance to ensure that some gentrification took place in most trials but did not overwhelm the entirety of the region. This operationalization also seems to fit common-sense notions of what it means for a neighborhood to be gentrified.

6. For simplicity, we conceive of each time tick as 1 year, but the time ticks may represent any relevant time designation.

7. Although we could have run each simulation longer, model testing revealed that price and quality trends stabilized at about tick 60, so we cut off the trials at this point; if thinking in terms of years, this suggests that we began the models around 1980 and concluded them at roughly 2020. See the appendix for more information.

8. Note that the finding that gentrification displacement is not affected by policy decisions regarding cleanup does not imply that other outcomes, such as environmental justice, are not affected by them.

Additional information

Notes on contributors

Adam Eckerd

Adam Eckerd is an assistant professor in the School of Public and Environmental Affairs at IUPUI. He conducts research on organizational and individual decision making, particularly as it relates to how risk is assessed and how information is used to manage public and nonprofit programs and policies. Adam’s work investigates issues of environmental justice, public participation, and program evaluation. His research articles appear in various outlets such as Urban Affairs Review, Policy Sciences, Public Administration Review, American Review of Pubic Administration, American Journal of Evaluation, and Review of Policy Research.

Yushim Kim

Yushim Kim is an associate professor in the School of Public Affairs, a Senior Sustainability Scholar at Julie Ann Wrigley Global Institute of Sustainability, and a Graduate Faculty in Complex Adaptive Systems Science at Arizona State University. Her research focuses on environmental justice and policy, public health emergency response, and welfare fraud. Her research articles appear in journals such as Urban Studies, Administration & Society, Policy Sciences, Disaster Medicine and Public Health Preparedness, Social Science Quarterly, Journal of Artificial Societies and Social Simulation.

Heather Campbell

Heather Campbell is chair and professor in the Department of Politics and Government at the Claremont Graduate University. Her research focuses on urban environmental policy analysis with a particular focus on environmental justice. She has published two books on these topics, Urban Environmental Policy Analysis (Campbell and Corley 2012) and Rethinking Environmental Justice in Sustainable Cities: Insights from Agent-Based Modeling (Campbell, Kim and Eckerd 2015). Her research articles appear in outlets such as Environment and Planning B, Review of Policy Research, Urban Affairs Review, Journal of Urban Affairs, and Journal of Regional Science.